Mammalian circadian systems: Organization and modern life challenges

Humans and other mammalian species possess an endogenous circadian clock system that has evolved in adaptation to periodically reoccurring environmental changes and drives rhythmic biological functions, as well as behavioural outputs with an approximately 24-hour period. In mammals, body clocks are hierarchically organized, encompassing a so-called pacemaker clock in the hypothalamic suprachiasmatic nucleus (SCN), non-SCN brain and peripheral clocks, as well as cell-autonomous oscillators within virtually every cell type. A functional clock machinery on the molecular level, alignment among body clocks, as well as synchronization between endogenous circadian and exogenous environmental cycles has been shown to be crucial for our health and well-being. Yet, modern life constantly poses widespread challenges to our internal clocks,for exampleartificial lighting, shift work and trans-meridian travel, potentially leading to circadian disruption or misalignment and the emergence of associated diseases. For instance many of us experience a mismatch between sleep timing on work and free days (social jetlag) in our everyday lives without being aware of health consequences that may arise from such chronic circadian misalignment, Hence, this review provides an overview of the organization and molecular built-up of the mammalian circadian system, its interactions with the outside world, as well as pathologies arising from circadian disruption and misalignment

Venn diagram analysis overestimates the extent of circadian rhythm reprogramming

The circadian clock modulates key physiological processes in many organisms. This widespread role of circadian rhythms is typically characterized at the molecular level by profiling the transcriptome at multiple time points. Subsequent analysis identifies transcripts with altered rhythms between control and perturbed conditions, that is, are differentially rhythmic (DiffR). Commonly, Venn diagram analysis (VDA) compares lists of rhythmic transcripts to catalog transcripts with rhythms in both conditions, or that have gained or lost rhythms. However, unavoidable errors in rhythmicity detection propagate to the final DiffR classification resulting in overestimated DiffR. We show using artificial experiments on biological data that VDA indeed produces excessive false DiffR hits both in the presence and absence of true DiffR transcripts. We review and benchmark hypothesis testing and model selection approaches that instead compare circadian amplitude and phase of transcripts between the two conditions. These methods identify transcripts that ‘gain’, ‘lose’, ‘change’, or have the ‘same’ rhythms; the third category is missed by VDA. We reanalyzed three studies on the interplay between metabolism and the clock in the mouse liver that used VDA. We found not only fewer DiffR transcripts than originally reported, but VDA overlooked many relevant DiffR transcripts. Our analyses confirmed some and contradicted other conclusions in the original studies and also generated novel insights. Our conclusions equally apply to circadian studies using other omics technologies. We believe that avoiding Venn diagrams and using our convenient r‐package comparerhythms will improve the reliability of analyses in chronobiology.Comparing rhythms with and without an intervention reveals the functioning of the circadian system. High‐throughput studies of clock outputs (transcripts, proteins, etc.) typically compare lists of rhythmic outputs in each condition using Venn diagrams. This approach incorrectly predicts too many altered rhythms, while also overlooking some rhythm changes. Direct comparison of amplitudes and phases using R‐package comparerhythms fixes this problem and reveals limited circadian remodeling due to metabolic changes. imageDeutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659Peer Reviewe

Reliability Evaluation of Drivetrains: Challenges for Off‐ Highway Machines

Downtime of mobile machinery used in fields like construction, earthmoving or mining usually leads to an instant halt of an entire process and can even endanger entire operations. To meet the customer’s requirement for high availabilities of their equipment, safeguarding the reliability of overall systems and components is necessary. Since life expectancy of systems and its components strongly depends on the experienced load history, this information needs to be available as accurately as possible to allow reliable lifetime calculation results. Due to the wide range of machines and applications of off‐highway machines, determining representative loads is especially challenging. The challenges, in determining both load cycles for the entire system and local component loads, are discussed in this work, along with approaches to face them. Additionally, a method is described, which allows users to quantitatively calculate life expectancy of technical systems in both the concept phase and the later stages of the product life cycle. In the end, two examples are presented in which exemplary challenges are faced

Feedback Loops of the Mammalian Circadian Clock Constitute Repressilator

Mammals evolved an endogenous timing system to coordinate their physiology and behaviour to the 24h period of the solar day. While it is well accepted that circadian rhythms are generated by intracellular transcriptional feedback loops, it is still debated which network motifs are necessary and sufficient for generating self-sustained oscillations. Here, we systematically explore a data-based circadian oscillator model with multiple negative and positive feedback loops and identify a series of three subsequent inhibitions known as “repressilator” as a core element of the mammalian circadian oscillator. The central role of the repressilator motif is consistent with time-resolved ChIP- seq experiments of circadian clock transcription factors and loss of rhythmicity in core clock gene knockouts

Protein Phosphatase 1 (PP1) Is a Post-Translational Regulator of the Mammalian Circadian Clock

Circadian clocks coordinate the timing of important biological processes. Interconnected transcriptional and post-translational feedback loops based on a set of clock genes generate and maintain these rhythms with a period of about 24 hours. Many clock proteins undergo circadian cycles of post-translational modifications. Among these modifications, protein phosphorylation plays an important role in regulating activity, stability and intracellular localization of clock components. Several protein kinases were characterized as regulators of the circadian clock. However, the function of protein phosphatases, which balance phosphorylation events, in the mammalian clock mechanism is less well understood. Here, we identify protein phosphatase 1 (PP1) as regulator of period and light-induced resetting of the mammalian circadian clock. Down-regulation of PP1 activity in cells by RNA interference and in vivo by expression of a specific inhibitor in the brain of mice tended to lengthen circadian period. Moreover, reduction of PP1 activity in the brain altered light-mediated clock resetting behavior in mice, enhancing the phase shifts in either direction. At the molecular level, diminished PP1 activity increased nuclear accumulation of the clock component PER2 in neurons. Hence, PP1, may reduce PER2 phosphorylation thereby influencing nuclear localization of this protein. This may at least partially influence period and phase shifting properties of the mammalian circadian clock

Parallel monitoring of RNA abundance, localisation and compactness with correlative single molecule FISH on LR White embedded samples

Single mRNA molecules are frequently detected by single molecule fluorescence in situ hybridization (smFISH) using branched DNA technology. While providing strong and background-reduced signals, the method is inefficient in detecting mRNAs within dense structures, in monitoring mRNA compactness and in quantifying abundant mRNAs. To overcome these limitations, we have hybridized slices of high pressure frozen, freeze-substituted and LR White embedded cells (LR White smFISH). mRNA detection is physically restricted to the surface of the resin. This enables single molecule detection of RNAs with accuracy comparable to RNA sequencing, irrespective of their abundance, while at the same time providing spatial information on RNA localization that can be complemented with immunofluorescence and electron microscopy, as well as array tomography. Moreover, LR White embedding restricts the number of available probe pair recognition sites for each mRNA to a small subset. As a consequence, differences in signal intensities between RNA populations reflect differences in RNA structures, and we show that the method can be employed to determine mRNA compactness. We apply the method to answer some outstanding questions related to trans-splicing, RNA granules and mitochondrial RNA editing in single-cellular trypanosomes and we show an example of differential gene expression in the metazoan Caenorhabditis elegans

Synchronization-Induced Rhythmicity of Circadian Oscillators in the Suprachiasmatic Nucleus

The suprachiasmatic nuclei (SCN) host a robust, self-sustained circadian pacemaker that coordinates physiological rhythms with the daily changes in the environment. Neuronal clocks within the SCN form a heterogeneous network that must synchronize to maintain timekeeping activity. Coherent circadian output of the SCN tissue is established by intercellular signaling factors, such as vasointestinal polypeptide. It was recently shown that besides coordinating cells, the synchronization factors play a crucial role in the sustenance of intrinsic cellular rhythmicity. Disruption of intercellular signaling abolishes sustained rhythmicity in a majority of neurons and desynchronizes the remaining rhythmic neurons. Based on these observations, the authors propose a model for the synchronization of circadian oscillators that combines intracellular and intercellular dynamics at the single-cell level. The model is a heterogeneous network of circadian neuronal oscillators where individual oscillators are damped rather than self-sustained. The authors simulated different experimental conditions and found that: (1) in normal, constant conditions, coupled circadian oscillators quickly synchronize and produce a coherent output; (2) in large populations, such oscillators either synchronize or gradually lose rhythmicity, but do not run out of phase, demonstrating that rhythmicity and synchrony are codependent; (3) the number of oscillators and connectivity are important for these synchronization properties; (4) slow oscillators have a higher impact on the period in mixed populations; and (5) coupled circadian oscillators can be efficiently entrained by light–dark cycles. Based on these results, it is predicted that: (1) a majority of SCN neurons needs periodic synchronization signal to be rhythmic; (2) a small number of neurons or a low connectivity results in desynchrony; and (3) amplitudes and phases of neurons are negatively correlated. The authors conclude that to understand the orchestration of timekeeping in the SCN, intracellular circadian clocks cannot be isolated from their intercellular communication components

The impact of daylight‐saving time (DST) on patients with delayed sleep‐wake phase disorder (DSWPD)

Due to time zones, sun time and local time rarely match. The difference between local and sun time, which we designate by Solar Jet Lag (SoJL), depends on location within a time zone and can range from zero to several hours. Daylight Saving Time (DST) simply adds one hour to SoJL, independent of location. We hypothesized that the impact of DST, is particularly problematic in patients with Delayed Sleep-Wake Phase Disorder (DSWPD), worsening their sleep debt. DSWPD is characterized by a chronic misalignment between the internal and social timing, reflected by an inability to fall asleep and wakeup at conventional or socially acceptable times. We analysed the clinical records of 162 DSWPD patients from a sleep medicine centre in Lisbon, Portugal (GMTzone), and separated them into two groups: the ones diagnosed across DST or Standard Time (ST). We included 82 patients (54.9% male; age: median [Q1, Q3] 34.5 [25.0, 45.3]; range 16-92; 54 in DST and 28 in ST) who had Dim Light Melatonin Onset (DLMO) measured as a marker for the circadian phase and sleep timing (onset, SO, mid-point, MS and end, SE) self-reported separately for work- and work-free days. Differences between ST and DST were compared using Mann-Whitney or Student's t tests. On a weekly average, patients in DST slept an hour less (62 min. pinfo:eu-repo/semantics/acceptedVersioninfo:eu-repo/semantics/publishedVersio